Autopilot

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Problem Statement

How can we simplify the process of maximizing flight point redemption for travelers with flight reward program(s) so that they can fly more for less?

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Problem Background

In an era marked by a surge in global connectivity and a heightened desire for exploration, travel has transcended from a luxury to a lifestyle. Fueling this wanderlust are credit card and airline reward programs, promising a gateway to affordable adventures. Yet, as more individuals embrace the skies, the intricacies of maximizing the value of accumulated points have become a significant hurdle. 

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What is the need or problem we’re addressing?

The problem we’re addressing is the difficulty in finding optimal deals to maximize point redemption value and the challenges in securing available flights with points to target destinations. While conducting our own user research, 30% of travelers encountered challenges in locating favorable deals that maximized point redemption value, with 20% facing difficulties finding availability to use points for flights to their desired destinations. 

Evidently, travelers are facing hurdles in both securing advantageous deals and finding point availability for specific target destinations, contributing to the frustrations experienced by most frequent travelers.

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How do we know this is a problem?

The problem has been identified through extensive user interviews/surveys and market research. Travelers have expressed their frustrations with the current flight point redemption process and their desire for a more streamlined, automated approach. The fact that the majority of travelers perform manual calculations using a calculator to determine their point value, whilst still being affected by point devaluations unknowingly, challenges the efficiency and effectiveness of point redemption, making it more difficult for individuals to optimize their rewards for travel, underscoring the need for a more effective solution.

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User Pain Points & Research Insights

At the core of our user research, travelers are finding it challenging to locate favorable deals that maximize point redemption value and finding availability to redeem flights with points to their desired destination. For instance, Rick struggles with determining the best way to efficiently maximize his point value during the redemption process, while one user responds that the “lack of availability” frustrates them. These insights, combined with the fact that 50% of travelers found it challenging to redeem their points for complimentary flights contribute to frustrations in flying more for less. 

Supporting User Data 

• Traveler Motivations: 90% of travelers engage in multiple trips annually, are also members of travel rewards programs, often redeem 40% of their flights with points. 
• Traveler Priorities: 80% of travelers prioritize redeeming flights with points. Additionally, 77.5% prioritize maximizing point redemption value.
• Point Redemption Experience: When redeeming points for flights, 80% of travelers check point value. 45% manually calculate with a calculator, and 7.5% use online tools (Excel & CPP calculator). For 75% of travelers, calculated value strongly influences flight redemption decisions. If they can maximize point value, 70% prefer using points.
• Point Value and Devaluation Awareness: 92.5% of travelers exhibit some degree of familiarity with point value, with 77.5% aware of point devaluations, and 12.5% that have no awareness at all.

Feedback 

Our research shows that 37.5% of travelers desire a product guiding them on the best time to use points for maximum redemption value, streamlining the process. They seek a tool eliminating manual efforts, advising on optimal flight redemption to maximize value. 

Landing on the Solution 

We propose a web extension that automates and streamlines the process of maximizing point redemption through efficient and real-time insights for point utilization. 

Explanation of Solution 

Our solution optimizes point redemption by providing real-time insights into point values, ensuring users maximize the value of their points for specific travel dates. It simplifies the point calculation process, making redemption effortless and hassle-free. Key features include:

• Maximize Point Redemption: Notification feature that informs travelers that they maximized their earned points for specific flight routes enabling efficient use of accumulated flight points.
• Real-time Insights: Displays point value per flight with a recommendation to redeem with points or cash based on current value and cash savings, to help travelers make an informed decision on point redemption.

Ultimately, the product aligns with users' goal of flying more for less, leveraging accumulated points for significant cost-savings and an enhanced travel experience.

Overview of the UX and Design

In developing the design, our priority was to ensure a seamless and intuitive user experience. We meticulously mapped out the user journey for booking flights on Air Canada, identifying key opportunities for our browser extension to enhance efficiency. Through several iterations—guided by team insights and user feedback—we refined the design to align with our goals of intuitiveness and minimal disruption. These incremental adjustments were crucial in ensuring that the design not only met but exceeded user expectations for simplicity and ease of use.

Lofi & Hifi Mock-ups

Final MVP

Check out our prototype here!

Iterative Design Learnings

As we designed iteration after iteration, certain key takeaways became apparent:

• Engage with users. After completing the initial user tests, we were struck by the number of blind spots identified by participants. Soliciting feedback from frequent flyers allowed us to refine the design to better meet their expectations and needs.
• Users are value driven. They want to quickly know what’s best. Our users are primarily bargain hunters who want clear information on their savings. They are driven by the desire to get the most value from their flights, with the primary concern being which payment method offers the greatest savings.
• Users are highly focused on data and accuracy. Users meticulously analyze all provided data. When designing data visualizations, it's crucial that every element on the interface is intentional and offers clear value to the user, ensuring both accuracy and utility.

Technical Implementation

Where is it hosted? 

• Our Chrome extension isn't hosted in the traditional sense on a server. Instead, it resides locally on the user's machine within their Chrome browser. The source code could be distributed through the Chrome Web Store, where users can download and install it.

What is your tech stack? 

• Frontend: HTML, CSS, and JavaScript are used for building the popup and content scripts of the Chrome extension. This includes manipulating the DOM based on user interactions and displaying data.
• Backend: For additional processing that requires external API interaction (e.g., fetching airport data), you mentioned an Express.js server. This server runs Node.js and communicates with external APIs.
• CSS Frameworks: There wasn't a specific mention of a CSS framework like Bootstrap or Tailwind CSS, so it's assumed plain CSS is used for styling.
• Database Choice: No database is explicitly mentioned for storing any persistent data locally or on a server. Data seems to be fetched real-time from APIs and displayed directly.
• Other Tools: Node-fetch for server-side requests in Node.js, Chrome APIs for message passing between different parts of the extension.

High Level Journey of a Request

• User Interaction: A user clicks a button in the extension's popup or in the content loaded by the extension within a webpage.
• Message Passing: Actions from the popup trigger messages sent to content scripts or the background script (e.g., fetching flight details).
• Data Handling: Content scripts manipulate the DOM of the web page or send requests back to the popup to display data. If external data is needed, the background or server-side script fetches data from an API.
• Response Display: The popup or content script receives the data and updates the DOM to display new information, such as flight details or airport information.

Why We Chose These Tools

• Use of a Framework: Introducing frameworks like React for the popup could enhance the UI's responsiveness and maintainability.
• Caching Responses: Implementing caching either in the browser storage or within your backend can reduce API call frequency, improving response times and reducing load on external services.
• Error Handling: Enhancing error handling and adding more robust mechanisms for dealing with API downtime or rate limiting.

Technical Challenges

What was the hardest part of development?

• Cross-Origin Resource Sharing (CORS): Handling CORS by moving API requests to a backend server was a significant challenge
• Scalability: If the user base grows, the server-side component making API requests might need to handle more requests, potentially leading to rate limiting issues with the APIs used.
• State Management: Managing the state across different scripts (popup, content, background) in a Chrome extension can be complex without a robust framework.

Achievements 

When asked, “On a scale of 1-5, how useful did you find Autopilot?”users gave our product a rating of 4.2/5! And when asked, “On a scale of 0-10, how likely are you to recommend our product to friends or colleagues, 60% of users rated 8 or higher! 

This data paints a clear picture that our product is targeting the right solution for the right problem, and that users are enjoying the utility provided with our extension! 

Future Steps 

Our ultimate vision for Autopilot is to revolutionize the flight point redemption process for travelers on all airline and credit card reward programs - ensuring travelers maximize their rewards for more exciting adventures! 

Given the positive reception and excitement with our product, our team is excited to continue working on Autopilot. Our goal from the beginning of this program was to deliver a functional MVP that includes just enough core features to satisfy our early adopters and we stand by that! We look forward to building out this product further and publicly releasing it on the chrome web store!

Contact Us 

If you like our work or want to learn more about our journey with Autopilot, please reach out to us! 

• PM: John Miranda | LinkedIn, Portfolio
• Designer: Antoni Ngo | Linkedin, Portfolio
• Developer: Ethan Harrington | Linkedin
• Developer: Andrew Capaldo | Linkedin
• Mentor: Aniththa Umamahesan | LinkedIn

Thanks for reading our story and we look forward to hearing from you!

Other documents

• ‍Research Plan ‍
• Research Synthesis ‍
• Research Synthesis Presentation ‍
• Survey Link